Merge branch 'dev' into d/announcement-update

agents-api/agents_api/activities/task_steps/prompt_step.py

@@ -22,7 +22,6 @@ async def prompt_step(context: StepContext) -> StepOutcome:
         context_data,
         skip_vars=["developer_id"],
     )
-
     # Get settings and run llm
     agent_default_settings: dict = (
         context.execution_input.agent.default_settings.model_dump()

agents-api/agents_api/activities/task_steps/tool_call_step.py

@@ -1,20 +1,49 @@
+import base64
+import secrets
+
 from beartype import beartype
 from temporalio import activity
 
+from ...activities.task_steps import base_evaluate
+from ...autogen.openapi_model import ToolCallStep
 from ...common.protocol.tasks import (
     StepContext,
+    StepOutcome,
 )
 
 
+def generate_call_id():
+    # Generate 18 random bytes (which will result in 24 base64 characters)
+    random_bytes = secrets.token_bytes(18)
+    # Encode to base64 and remove padding
+    base64_string = base64.urlsafe_b64encode(random_bytes).decode("ascii").rstrip("=")
+    # Add the "call_" prefix
+    return f"call_{base64_string}"
+
+
 @activity.defn
 @beartype
-async def tool_call_step(context: StepContext) -> dict:
-    raise NotImplementedError()
-    # assert isinstance(context.current_step, ToolCallStep)
+async def tool_call_step(context: StepContext) -> StepOutcome:
+    assert isinstance(context.current_step, ToolCallStep)
+
+    tool_type, tool_name = context.current_step.tool.split(".")
+    arguments = await base_evaluate(
+        context.current_step.arguments, context.model_dump()
+    )
+
+    tools = context.execution_input.tools
+
+    assert tool_name in [tool.name for tool in tools], f"Tool {tool_name} not found"
+
+    call_id = generate_call_id()
 
-    # context.current_step.tool_id
-    # context.current_step.arguments
-    # # get tool by id
-    # # call tool
+    tool_call = {
+        tool_type: {
+            "arguments": arguments,
+            "name": tool_name,
+        },
+        "id": call_id,
+        "type": tool_type,
+    }
 
-    # return {}
+    return StepOutcome(output=tool_call)

agents-api/agents_api/common/protocol/tasks.py

@@ -72,7 +72,7 @@
     "error": [],
     "cancelled": [],
     # Intermediate states
-    "wait": ["resume", "cancelled", "finish", "finish_branch"],
+    "wait": ["resume", "step", "cancelled", "finish", "finish_branch"],
     "resume": [
         "wait",
         "error",

agents-api/agents_api/workflows/task_execution/__init__.py

@@ -81,7 +81,7 @@
 # Mapping of step types to their corresponding activities
 STEP_TO_ACTIVITY = {
     PromptStep: task_steps.prompt_step,
-    # ToolCallStep: tool_call_step,
+    ToolCallStep: task_steps.tool_call_step,
     WaitForInputStep: task_steps.wait_for_input_step,
     SwitchStep: task_steps.switch_step,
     LogStep: task_steps.log_step,
@@ -389,10 +389,7 @@ async def run(
 
                 state = PartialTransition(type="resume", output=result)
 
-            case PromptStep(), StepOutcome(
-                output=response
-            ):  # FIXME: if not response.choices[0].tool_calls:
-                # SCRUM-15
+            case PromptStep(), StepOutcome(output=response):
                 workflow.logger.debug(f"Prompt step: Received response: {response}")
                 if response["choices"][0]["finish_reason"] != "tool_calls":
                     workflow.logger.debug("Prompt step: Received response")
@@ -421,19 +418,6 @@ async def run(
                     )
                     state = PartialTransition(output=new_response.output, type="resume")
 
-            # case PromptStep(), StepOutcome(
-            #     output=response
-            # ):  # FIXME: if response.choices[0].tool_calls:
-            #     # SCRUM-15
-            #     workflow.logger.debug("Prompt step: Received response")
-            #
-            #     ## First, enter a wait-for-input step and ask developer to run the tool calls
-            #     ## Then, continue the workflow with the input received from the developer
-            #     ## This will be a dict with the tool call name as key and the tool call arguments as value
-            #     ## The prompt is run again with the tool call arguments as input
-            #     ## And the result is returned
-            #     ## If model asks for more tool calls, repeat the process
-
             case SetStep(), StepOutcome(output=evaluated_output):
                 workflow.logger.info("Set step: Updating user state")
                 self.update_user_state(evaluated_output)
@@ -466,11 +450,15 @@ async def run(
                 workflow.logger.error("ParallelStep not yet implemented")
                 raise ApplicationError("Not implemented")
 
-            case ToolCallStep(), _:
-                # FIXME: Implement ToolCallStep
-                # SCRUM-16
-                workflow.logger.error("ToolCallStep not yet implemented")
-                raise ApplicationError("Not implemented")
+            case ToolCallStep(), StepOutcome(output=tool_call):
+                # Enter a wait-for-input step to ask the developer to run the tool calls
+                tool_call_response = await workflow.execute_activity(
+                    task_steps.raise_complete_async,
+                    args=[context, tool_call],
+                    schedule_to_close_timeout=timedelta(days=31),
+                )
+
+                state = PartialTransition(output=tool_call_response, type="resume")
 
             case _:
                 workflow.logger.error(
@@ -502,7 +490,7 @@ async def run(
 
         # Continue as a child workflow
         return await continue_as_child(
-            context,
+            context.execution_input,
             start=final_state.next,
             previous_inputs=previous_inputs + [final_state.output],
             user_state=self.user_state,